code: def test_shuffle_bytes(mode, stride, window_size) -> None:
      opts = argparse.Namespace()
      setattr(opts, "image_augmentation.shuffle_bytes.mode", mode)
      setattr(opts, "image_augmentation.shuffle_bytes.stride", stride)
      setattr(
          opts,
          "image_augmentation.shuffle_bytes.window_size",
          window_size,
      )
  
      t = image_bytes.ShuffleBytes(opts)
  
      size = 32
      samples = torch.randint(255, [size])
      x = {"samples": samples.clone()}
      out = t(x)["samples"]
      assert torch.any(samples != out)
      assert samples.sum() == out.sum()
  
file_path: ml-cvnets/tests/transforms/test_image_bytes.py
imports: import argparse
  from typing import Tuple
  import pytest
  import torch
  from data.transforms import image_bytes
label_desc: Use image node_id 2 for calling a global function with example usage: test_shuffle_bytes(mode, stride, window_size) without return types